Sea-Level Extremes At Four
New Zealand Tide Gauge Locations
And The Impact Of Future Sea-Level Rise
Research conducted for
Office of the Parliamentary Commissioner for the Environment
Wellington, New Zealand
J. R. Hunter
PO Box 3164, West Hobart, Tasmania 7000
28 August 2015
The information contained in this document is solely for the use of the client identified in
the report and for the purpose for which it has been prepared. No responsibility is accepted
to any third party who may rely upon this document.
The user of this data accepts any and all risks of such use, whether direct or indirect, and in
no event shall John Robert Hunter be liable for any damages and/or costs, including but
not limited to incidental or consequential damages of any kind, including economic damage
or loss or injury to person or property, regardless of whether John Robert Hunter shall be
advised, have reason to know, or in fact shall know of the possibility.
This work is copyright. It may be reproduced in whole or in part for research, study or
training purposes subject to the inclusion of an acknowledgment of the source, but not for
commercial sale or use.
Contents
1 Introduction
1
2 Caveats
1
3 The Derivation of Sea-Level Planning Allowances
2
4 The Input Data
5
4.1
Sea-Level Rise Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5
4.2
Tide-Gauge Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
4.3
Historic Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
5 Results
8
5.1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
5.2
Extremes Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
5.3
Sea-Level Rise Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
5.4
Sea-Level Planning Allowances . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
5.5
Future Average Recurrence Intervals . . . . . . . . . . . . . . . . . . . . . . .
9
6 Glossary of Terms
38
Appendix A Copy of Contract
40
List of Tables
1
Summary of tide-gauge data and derived Gumbel parameters . . . . . . . . . .
8
2
Model sea-level projections, and allowances for Auckland under RCP4.5 . . . .
14
3
Model sea-level projections, and allowances for Dunedin under RCP4.5 . . . .
15
4
Model sea-level projections, and allowances for Lyttleton under RCP4.5 . . . .
16
5
Model sea-level projections, and allowances for Wellington under RCP4.5 . . .
17
6
Effective average recurrence intervals (EARIs) for Auckland under RCP4.5
using the ‘very likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . .
18
Effective average recurrence intervals (EARIs) for Auckland under RCP4.5
using the ‘likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . .
19
Effective average recurrence intervals (EARIs) for Dunedin under RCP4.5 using
the ‘very likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . .
20
Effective average recurrence intervals (EARIs) for Dunedin under RCP4.5 using
the ‘likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21
Effective average recurrence intervals (EARIs) for Lyttleton under RCP4.5 using the ‘very likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . .
22
Effective average recurrence intervals (EARIs) for Lyttleton under RCP4.5 using the ‘likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
23
Effective average recurrence intervals (EARIs) for Wellington under RCP4.5
using the ‘very likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . .
24
Effective average recurrence intervals (EARIs) for Wellington under RCP4.5
using the ‘likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . .
25
14
Model sea-level projections, and allowances for Auckland under RCP8.5 . . . .
26
15
Model sea-level projections, and allowances for Dunedin under RCP8.5 . . . .
27
16
Model sea-level projections, and allowances for Lyttleton under RCP8.5 . . . .
28
17
Model sea-level projections, and allowances for Wellington under RCP8.5 . . .
29
18
Effective average recurrence intervals (EARIs) for Auckland under RCP8.5
using the ‘very likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . .
30
Effective average recurrence intervals (EARIs) for Auckland under RCP8.5
using the ‘likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . .
31
Effective average recurrence intervals (EARIs) for Dunedin under RCP8.5 using
the ‘very likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . .
32
7
8
9
10
11
12
13
19
20
21
22
23
24
25
Effective average recurrence intervals (EARIs) for Dunedin under RCP8.5 using
the ‘likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
33
Effective average recurrence intervals (EARIs) for Lyttleton under RCP8.5 using the ‘very likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . .
34
Effective average recurrence intervals (EARIs) for Lyttleton under RCP8.5 using the ‘likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
35
Effective average recurrence intervals (EARIs) for Wellington under RCP8.5
using the ‘very likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . .
36
Effective average recurrence intervals (EARIs) for Wellington under RCP8.5
using the ‘likely’ assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . .
37
List of Figures
1
Regional projections of sea-level rise between 1986-2005 and 2081-2100 from
the AR5, based on the RCP4.5 Representative Concentration Pathway . . . .
6
2
Locations of grid points of IPCC AR5 sea-level projections and tide-gauge sites
7
3
Average recurrence intervals (ARIs) and heights for Auckland for 2015 . . . .
10
4
Average recurrence intervals (ARIs) and heights for Dunedin for 2015 . . . . .
11
5
Average recurrence intervals (ARIs) and heights for Lyttleton for 2015
. . . .
12
6
Average recurrence intervals (ARIs) and heights for Wellington for 2015 . . . .
13
1
Introduction
The work described in this document was commissioned by the Office of the Parliamentary
Commissioner for the Environment (OPCE), Wellington, New Zealand, in July 2015 (see
Appendix A). Summarising, the key tasks were to:
1. Calculate the Gumbel scale parameter of storm-tide extremes from the tide-gauge
data provided.
2. Calculate the best estimate and standard deviation of sea-level rise during this
century, based on the projections of the Fifth Assessment Report (AR5) of the
Intergovernmental Panel on Climate Change (IPCC) for RCP4.5 and RCP8.5.
3. Calculate sea-level planning allowances to accommodate future sea-level rise.
4. Calculate future average recurrence intervals (ARIs, also known as return periods),
based on a range of present-day ARIs, each of which is prescribed by a specific vertical
height. This includes the peak heights of a number of nominated recent storm events.
The study follows closely the techniques described by Hunter (2012) and Hunter et al (2013).
2
Caveats
The methodology presented here is subject to a number of caveats:
a. These sea-level planning allowances only relate to the effect of sea-level rise on
inundation and not on the recession of soft (e.g. sandy) shorelines or on other impacts.
b. While these allowances include the effects of vertical land motion due to changes in
the Earth’s loading and gravitational field, caused by past and ongoing changes in
land ice (glacial isostatic adjustment (GIA) and the ‘gravitational fingerprint’
contribution, respectively), they do not include effects due to tectonic motion or local
land subsidence (produced, for example, by groundwater withdrawal); separate
allowances may need to be applied to account for these latter effects.
c. These allowances are based on the assumption that the statistics of the storm tides will
not change in time. This is supported by the fact that present evidence (Bindoff et al,
2007, Lowe et al, 2012, Menéndez and Woodworth, 2010, Woodworth and Blackman,
2004) suggests that the rise in mean sea level is generally the dominant cause of any
observed increase in the frequency of inundation events. In addition, using model
projections of storm tides in southeast Australia to 2070, McInnes et al (2009) showed
that the increase in the frequency of inundation events was dominated by sea-level rise.
d. These allowances include no contribution due to possible changes in wave setup or
runup.
e. These allowances include no contribution due to the change in tides caused by sea-level
rise, which are generally small and confined to quite specific locations in shelf seas.
1
f. These allowances depend on an assumed probability distribution for the uncertainty of
the sea-level rise projections. Here, a normal or Gaussian distribution has been used,
which represents a pragmatic compromise between a tightly confined distribution, and
one with a fat upper tail (i.e. one in which there is a low probability of having a very
high sea-level rise relative to the best estimate of that rise). The allowances represent
a practical solution to planning for sea-level rise while preserving an acceptable level of
inundation likelihood, in cases where ‘getting the allowance wrong’ is manageable.
However, in cases where the consequence of inundation would be ‘dire’ (in the sense
that the consequence of inundation would be unbearable, no matter how low the
likelihood, as in case of the Netherlands), a precautionary approach would be not to
use the allowances presented here, but to base an allowance on the best estimate of
the maximum possible rise.
g. Two versions of each allowance and average recurrence interval are given: one denoted
‘very likely’ and the other denoted ‘likely’. The ‘very likely’ version involves the
assumption that the ‘very likely’ (5-95%) range of model uncertainty approximates the
‘very likely’ (5-95%) range of projection uncertainty. The ‘likely’ version is a more
conservative estimate, involving the assumption that not all the uncertainty is
captured by the models so that the ‘very likely’ (5-95%) range of model uncertainty
approximates the ‘likely’ (17-83%) range of projection uncertainty. The arguments
supporting the ‘likely’ assumption were presented by the Fourth and Fifth Assessment
Reports (‘AR4’ and ‘AR5’, respectively) of the Intergovernmental Panel on Climate
Change (‘IPCC’), but the author does not find these entirely convincing. However, a
precautionary approach would be to use the ‘likely’ versions, which give slightly larger
allowances and smaller ARIs than the ‘very likely’ version.
3
The Derivation of Sea-Level Planning Allowances
The derivations described here summarise those of Hunter (2012) and Hunter et al (2013)
(which are almost identical), although the ordering of the equations has been changed
somewhat to relate more closely to the present study.
The method assumes that the sea-level extremes (from both tides and storm surges) can be
described by a Gumbel distribution, which is the the simplest of the generalised
extreme-value distributions (GEVs) and was used here because (1) it fits most sea-level
extremes quite well (e.g. van den Brink and Können, 2011) and (2) it yields a sea-level
planning allowance that is independent of the required level of precaution. The Gumbel
distribution relates the average recurrence interval, R, to the physical height, zP , (e.g. the
height of a critical part of a coastal asset) by:
zP − µ
R = exp
λ
(1)
where µ is a ‘location parameter’ and λ is a ‘scale parameter’.
The method assumes that there is no change in the variability of the extremes relative to
mean sea level, which implies that the value of the scale parameter, λ, does not change with
2
a rise in sea level. It is also assumed that there is no change in wave climate (and therefore
in wave setup and runup).
In this report, the ARI, R, is given in years. The location parameter, µ, is therefore the
height at which the ARI is exactly one year.
If mean sea level rises by a best estimate (or central value), ∆z, plus an uncertain amount,
z 0 , (which has a statistical distribution with zero mean and standard deviation, σu ), the ARI
becomes:
zP − µ − ∆z − z 0
R = exp
λ
!
0
(2)
The form of the distribution of z 0 is not well known but, for the present work, a normal or
Gaussian distribution has been assumed. This represents a pragmatic compromise between
a tightly confined distribution, and one with a fat upper tail (i.e. one in which there is a low
probability of having a very high sea-level rise relative to the best estimate of that rise).
Because of the presence of z 0 in Eq. 2, R0 can take many values for any single value of the
best estimate ∆z. However, an ‘effective’ estimate, R00 , may be derived by calculating the
average frequency of flooding events (i.e. the average value of 1/R0 ) over all z 0 and taking
the reciprocal of the result1 , giving:
zP − µ − A
R = exp
λ
00
(3)
where A is an ‘effective’ sea-level rise, given by:
A = ∆z +
σu2
2λ
(4)
(see Hunter (2012) or Hunter et al (2013) for a thorough derivation of this step).
The second term on the right-hand side of Eq. 4 is an additional amount of effective
sea-level rise required to cope with the uncertainty in the sea-level rise projections. As noted
above, the distribution of z 0 is here assumed to be normal or Gaussian; other distributions
yield similar equations to Eq. 4, but with a different form for the second term on the
right-hand side (which still depends on the width of the distribution and on the Gumbel
scale parameter, λ).
If the asset is now raised by an amount, B, the ARI becomes:
R000 = exp
zP + B − µ − A
λ
(5)
In order to preserve the average frequency of flooding events at the same value as it was
originally, R (Eq. 1) needs to be set equal to R000 (Eq. 5), requiring that B = A. The asset
1
Note that, for statistical reasons, the relevant variable to average is the frequency of flooding events rather
than its reciprocal (the ARI).
3
therefore needs to be raised by an amount equal to the ‘effective’ sea-level rise, A. This (A,
as given in Eq. 4) is therefore an appropriate sea-level planning allowance.
In the present work, two different estimates of σu are used, one denoted ‘very likely’ and the
other denoted ‘likely’. The ‘very likely’ estimate involves the assumption that the ‘very
likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of
projection uncertainty. This is equivalent to setting:
σu = σm
(6)
The ‘likely’ version is a more conservative estimate, involving the assumption that not all
the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of model
uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty. For a normal
or Gaussian distribution, this is equivalent to setting:
σu = 1.724σm
(7)
The arguments supporting the ‘likely’ assumption were presented by the IPCC AR4 and
AR5, but the author does not find these entirely convincing. However, a precautionary
approach would be to use the ‘likely’ versions, which give slightly larger allowances and
smaller ARIs than the ‘very likely’ version.
To summarise, the application of the above sea-level planning allowance ensures that the
expected, or average, number of extreme (inundation) events in a given period is preserved
under sea-level rise. In other words, any asset raised by this allowance would experience the
same frequency of inundation events under sea-level rise as it would without the allowance
and without sea-level rise. It is important to note that this allowance only relates to the
effect of sea-level rise on inundation and not on the recession of soft (e.g. sandy) shorelines
or on other impacts.
In the terminology of risk assessment (e.g. ISO, 2009), the expected number of inundation
events in a given period is known as the likelihood. If a specific cost may be attributed to
one inundation event, then this cost is termed the consequence, and the combined effect
(generally the product) of the likelihood and the consequence is the risk (i.e. the total
effective cost of damage from inundation over the given period). The allowance is therefore
the height that an asset needs to be raised under sea-level rise in order to keep the
inundation risk the same.
An important property of the allowance is that it is independent of the required level of
precaution. In the case of coastal infrastructure, an appropriate height should first be
selected, based on present conditions and an acceptable degree of precaution (e.g. an
average of one inundation event in 100 years). If this height is then raised by the allowance
calculated for a specific period, the required level of precaution will be sustained until the
end of this period.
The planning allowances and future effective average recurrence intervals (EARIs) derived
here are based on the following information:
1. the IPCC AR5 regional projections of sea-level rise for RCP4.5 and RCP8.5, and
4
2. the statistics of storm tide extremes (specifically the Gumbel scale parameter) for
tide-gauge observations at Auckland, Dunedin, Lyttleton and Wellington.
4
The Input Data
4.1
Sea-Level Rise Projections
This study used the regional projections of the IPCC AR5, which were forced by
atmospheric concentrations of greenhouse gases and aerosols, rather than by the emission
scenarios used by the AR4. The atmospheric concentrations are characterised by
Representative Concentration Pathways or RCPs. The allowances presented here are based
on RCP4.5 and RCP8.5, which are roughly equivalent to the B1 and A1FI SRES2 emission
scenarios, respectively (Wayne, 2013). The world is broadly following A1FI at present
(Le Quéré et al, 2009)). RCP8.5 is the highest-emission RCP presented in the AR5.
The AR5 presented regional projections of relative sea-level rise3 , including the effects of
past and future changes of ice on land (glacial isostatic adjustment (GIA) and the
‘gravitational fingerprint’ contribution, respectively). As an example, Figure 1 shows
regional projections of sea-level rise between 1986-2005 and 2081-2100 from the AR5, based
on the RCP4.5 Representative Concentration Pathway (Church et al, 2013).
The results presented here were based on annual time series of the AR5 sea-level projections
for RCP4.5 and RCP8.5 over the 21st century, defined on a 1◦ longitude × 1◦ latitude grid.
They were downloaded from:
http://icdc.zmaw.de/thredds/catalog/ftpthredds/ar5_sea_level_rise/catalog.html
on 22/7/2014.
Figure 2 shows New Zealand with the locations of the sea-level projections shown as black
dots. Also shown are the tide-gauge locations (red dots).
The AR5 sea-level rise projections were interpolated to the four tide-gauge locations using
variants of linear interpolation, depending on the number of ‘model’ points surrounding each
coastal point. One component of the total sea-level rise, the glacial isostatic adjustment or
GIA, was treated in a slightly different way, because it is available over the whole Earth (i.e.
at the black dots shown in Figure 2 plus the remaining locations that would complete the
‘checker-board’ pattern). GIA can therefore be interpolated at the coastal locations using all
four nearest neighbours and bilinear interpolation. Two sets of coastal sea-level projections
have therefore been computed:
1. projections based on linear interpolation of the regional sea-level projections, using
ocean points only, and
2
3
Special Report on Emission Scenarios; Nakicenovic et al, 2000.
‘Relative sea-level rise’ is the sea-level rise relative to the land.
5
Figure 1: Regional projections of sea-level rise between 1986-2005 and 2081-2100 from the
AR5, based on the RCP4.5 Representative Concentration Pathway. (a) is the global mean,
(b) the 5-percentile lower bound and (c) the 95-percentile upper bound. From Church et al
(2013), Figure 13.19.
6
AUCKLAND
WELLINGTON
LYTTLETON
DUNEDIN
Figure 2: Locations of grid points of IPCC AR5 sea-level projections (black) and tide-gauge
sites (red).
7
2. projections based of linear interpolation of the regional sea-level projections without
GIA, using ocean points only, plus bilinear interpolation of GIA projections, using
ocean and land points.
The coastal projections (2) are generally better than (1) because the interpolation uses more
data (the GIA points over the land). Also, the difference in the resulting allowances is small
(i.e. at the millimetre level) and for the results presented here, the corrected projections (2)
have been used.
4.2
Tide-Gauge Data
Tide-gauge records for Auckland, Dunedin, Lyttleton and Wellington were provided by
OPCE in CSV format via dropbox4 on 7/7/2015. Table 1 summarises the tide-gauge data.
Location
Longitude Latitude
Auckland
Dunedin
Lyttleton
Wellington
174◦ 46’
170◦ 30’
172◦ 43’
174◦ 47’
E
E
E
E
36◦ 51’S
45◦ 53’S
43◦ 36’S
41◦ 17’S
Start
date
26/10/1903
31/12/1899
1/1/1924
1/1/1944
End
Gumbel location
Gumbel scale
date
parameter, µ (m) parameter, λ (m)
08/08/2014
1.966
0.0954
31/12/2013
1.494
0.0813
31/12/2012
1.660
0.0653
31/12/2013
1.121
0.0625
Table 1: Summary of tide-gauge data and derived Gumbel parameters.
4.3
Historic Events
Heights of historic sea-level events were provided by OPCE by email in the spreadsheet
NIWA Historic events.xlsx on 21/7/2015. Maximum heights of 16 events (3 for
Auckland, 4 for Dunedin, 5 for Lyttleton and 4 for Wellington) were recorded under the tab
‘Historic events’. Two heights were recorded for each event in columns headed ‘Sea-level
(m)’ and ‘Sea level with historic sea-level rise removed (m)’. All these heights were included
in the analysis described in Section 5.5. It was assumed (and confirmed be email from
OPCE on 22/7/2015) that the vertical datums used for these heights were the same as those
used for the respective tide gauges.
5
Results
5.1
Introduction
As advised by OPCE by email on 28/7/2015, the ‘present day’ is taken to be the start of
2015. This is the date to which the tide-gauge data and sea-level rise projections were
referenced.
4
https://www.dropbox.com/sh/b6rvgrmk3hxrtt9/AACk 0ros-szzDlmHBCyQxk6a?dl=0
8
5.2
Extremes Analysis
The tide-gauge records were initially detrended about the ‘present day’ (i.e. the start of
2015) using linear regression. Annual maxima of the tide-gauge records were then estimated
using a declustering algorithm such that any extreme events closer than 3 days were counted
as a single event, and any gaps in time were removed from the record. These annual
maxima were then fitted to a Gumbel distribution (see Section 3) using the ismev package
(Coles 2001, p. 48) implemented in the statistical language R (R Development Core Team
2008). This yielded the location and scale parameters, µ and λ (see Eq. 1), for each of the
four records; these values are shown in Table 1. The ARIs as a function of height are shown
in Figs. 3-6. All locations show a good fit to a Gumbel distribution, with the majority of
annual maxima (the dots) falling within the 95% confidence limits.
5.3
Sea-Level Rise Projections
The IPCC AR5 regional projections of sea-level rise are shown in Tables 2-5 (for RCP4.5)
and Tables 14-17 (for RCP8.5). The second column shows the ‘very likely’ (5-95%) range of
the model projections, and the third column shows the equivalent mean and standard
deviation, based on the assumption that the uncertainty distribution is normal or Gaussian.
5.4
Sea-Level Planning Allowances
The planning allowances (A of Eq. 4), using the ‘very likely’ and ‘likely’ assumptions are
shown in the fourth column of Tables 2-5 (for RCP4.5) and Tables 14-17 (for RCP8.5). The
allowances are similar during the early part of this century, but diverge significantly by
2100. As indicated in Section 3, the work of the IPCC AR5 suggests that the larger of these
(the ‘likely’ allowance) should be used.
5.5
Future Average Recurrence Intervals
Future ARIs were calculated using Eqs. 3 and 4, with µ and λ taken from Table 1, A taken
from Tables 2-5 (for RCP4.5) and Tables 14-17 (for RCP8.5) and zP equal to the specified
height. The heights consist of the extremes associated with the historic events (see
Section 4.3) plus additional ones selected every 0.10 m. The heights are ranked in ascending
order across the Tables.
9
2.6
2.5
Height above datum (m)
2.4
2.3
2.2
2.1
2
1.9
1.8
1.7
0.1
1
10
Average recurrence interval (years)
100
Figure 3: Average recurrence intervals (ARIs) and heights for Auckland for 2015. Continuous
line is best estimate and dashed lines are 95% confidence intervals. Dots indicate individual
annual maxima. The heights are above the local datum, which is the same as the datum of
the local tide-gauge record.
10
2.1
Height above datum (m)
2
1.9
1.8
1.7
1.6
1.5
1.4
1.3
0.1
1
10
Average recurrence interval (years)
100
Figure 4: Average recurrence intervals (ARIs) and heights for Dunedin for 2015. Continuous
line is best estimate and dashed lines are 95% confidence intervals. Dots indicate individual
annual maxima. The heights are above the local datum, which is the same as the datum of
the local tide-gauge record.
11
2.1
Height above datum (m)
2
1.9
1.8
1.7
1.6
1.5
0.1
1
10
Average recurrence interval (years)
100
Figure 5: Average recurrence intervals (ARIs) and heights for Lyttleton for 2015. Continuous
line is best estimate and dashed lines are 95% confidence intervals. Dots indicate individual
annual maxima. The heights are above the local datum, which is the same as the datum of
the local tide-gauge record.
12
1.6
Height above datum (m)
1.5
1.4
1.3
1.2
1.1
1
0.9
0.1
1
10
Average recurrence interval (years)
100
Figure 6: Average recurrence intervals (ARIs) and heights for Wellington for 2015. Continuous
line is best estimate and dashed lines are 95% confidence intervals. Dots indicate individual
annual maxima. The heights are above the local datum, which is the same as the datum of
the local tide-gauge record.
13
Year
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
2065
2070
2075
2080
2085
2090
2095
2100
Model projection
‘very likely’ range
5,95% (metres)
0.000, 0.000
0.015, 0.018
0.036, 0.051
0.058, 0.085
0.085, 0.123
0.108, 0.160
0.130, 0.186
0.129, 0.239
0.135, 0.301
0.165, 0.335
0.193, 0.359
0.202, 0.415
0.222, 0.447
0.236, 0.480
0.250, 0.532
0.255, 0.592
0.280, 0.633
0.300, 0.678
Model projection
Allowance, A
∆z, σm
‘very likely’, ‘likely’
(metres)
(metres)
0.000, 0.000
0.000, 0.000
0.017, 0.001
0.017, 0.017
0.043, 0.005
0.043, 0.044
0.072, 0.008
0.072, 0.073
0.104, 0.011
0.105, 0.106
0.134, 0.016
0.136, 0.138
0.158, 0.017
0.160, 0.163
0.184, 0.034
0.190, 0.202
0.218, 0.051
0.231, 0.258
0.250, 0.052
0.264, 0.291
0.276, 0.050
0.289, 0.315
0.309, 0.065
0.331, 0.374
0.335, 0.069
0.359, 0.408
0.358, 0.074
0.387, 0.444
0.391, 0.086
0.430, 0.506
0.424, 0.102
0.478, 0.587
0.457, 0.107
0.517, 0.635
0.489, 0.115
0.558, 0.694
Table 2: Model sea-level projections, and allowances for Auckland under RCP4.5. The third
column shows the range of model projections expressed as the best estimate (central value),
∆z, and standard deviation, σm . The ‘very likely’ allowance, A, involves the assumption that
the ‘very likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%)
range of projection uncertainty. The ‘likely’ allowance, A, is a more conservative estimate,
involving the assumption that not all the uncertainty is captured by the models so that the
‘very likely’ (5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of
projection uncertainty.
14
Year
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
2065
2070
2075
2080
2085
2090
2095
2100
Model projection
‘very likely’ range
5,95% (metres)
0.000, 0.000
0.020, 0.024
0.033, 0.063
0.055, 0.101
0.070, 0.138
0.102, 0.167
0.121, 0.197
0.129, 0.248
0.136, 0.300
0.167, 0.331
0.179, 0.357
0.189, 0.406
0.206, 0.462
0.236, 0.489
0.242, 0.532
0.241, 0.587
0.278, 0.636
0.291, 0.675
Model projection
Allowance, A
∆z, σm
‘very likely’, ‘likely’
(metres)
(metres)
0.000, 0.000
0.000, 0.000
0.022, 0.001
0.022, 0.022
0.048, 0.009
0.048, 0.050
0.078, 0.014
0.079, 0.081
0.104, 0.021
0.106, 0.112
0.134, 0.020
0.137, 0.141
0.159, 0.023
0.162, 0.168
0.189, 0.036
0.197, 0.212
0.218, 0.050
0.233, 0.263
0.249, 0.050
0.264, 0.294
0.268, 0.054
0.286, 0.322
0.297, 0.066
0.324, 0.377
0.334, 0.078
0.371, 0.444
0.362, 0.077
0.399, 0.471
0.387, 0.088
0.435, 0.529
0.414, 0.105
0.482, 0.617
0.457, 0.109
0.530, 0.673
0.483, 0.117
0.567, 0.732
Table 3: Model sea-level projections, and allowances for Dunedin under RCP4.5. The third
column shows the range of model projections expressed as the best estimate (central value),
∆z, and standard deviation, σm . The ‘very likely’ allowance, A, involves the assumption that
the ‘very likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%)
range of projection uncertainty. The ‘likely’ allowance, A, is a more conservative estimate,
involving the assumption that not all the uncertainty is captured by the models so that the
‘very likely’ (5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of
projection uncertainty.
15
Year
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
2065
2070
2075
2080
2085
2090
2095
2100
Model projection
‘very likely’ range
5,95% (metres)
0.000, 0.000
0.004, 0.011
0.024, 0.049
0.045, 0.092
0.072, 0.126
0.098, 0.145
0.111, 0.185
0.133, 0.221
0.145, 0.263
0.176, 0.304
0.185, 0.336
0.193, 0.368
0.218, 0.425
0.237, 0.450
0.256, 0.496
0.262, 0.546
0.296, 0.594
0.285, 0.634
Model projection
Allowance, A
∆z, σm
‘very likely’, ‘likely’
(metres)
(metres)
0.000, 0.000
0.000, 0.000
0.007, 0.002
0.007, 0.008
0.037, 0.008
0.037, 0.038
0.069, 0.014
0.070, 0.073
0.099, 0.016
0.101, 0.105
0.122, 0.014
0.123, 0.126
0.148, 0.022
0.152, 0.160
0.177, 0.027
0.183, 0.194
0.204, 0.036
0.214, 0.233
0.240, 0.039
0.251, 0.274
0.261, 0.046
0.277, 0.308
0.281, 0.053
0.302, 0.345
0.322, 0.063
0.352, 0.411
0.344, 0.065
0.376, 0.439
0.376, 0.073
0.416, 0.497
0.404, 0.087
0.461, 0.575
0.445, 0.091
0.508, 0.632
0.460, 0.106
0.546, 0.716
Table 4: Model sea-level projections, and allowances for Lyttleton under RCP4.5. The third
column shows the range of model projections expressed as the best estimate (central value),
∆z, and standard deviation, σm . The ‘very likely’ allowance, A, involves the assumption that
the ‘very likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%)
range of projection uncertainty. The ‘likely’ allowance, A, is a more conservative estimate,
involving the assumption that not all the uncertainty is captured by the models so that the
‘very likely’ (5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of
projection uncertainty.
16
Year
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
2065
2070
2075
2080
2085
2090
2095
2100
Model projection
‘very likely’ range
5,95% (metres)
0.000, 0.000
0.016, 0.023
0.032, 0.053
0.053, 0.093
0.066, 0.130
0.101, 0.154
0.117, 0.189
0.124, 0.221
0.133, 0.257
0.167, 0.299
0.185, 0.329
0.205, 0.364
0.213, 0.416
0.242, 0.429
0.240, 0.495
0.257, 0.532
0.280, 0.582
0.294, 0.623
Model projection
Allowance, A
∆z, σm
‘very likely’, ‘likely’
(metres)
(metres)
0.000, 0.000
0.000, 0.000
0.020, 0.002
0.020, 0.020
0.043, 0.006
0.043, 0.043
0.073, 0.012
0.074, 0.076
0.098, 0.020
0.101, 0.107
0.128, 0.016
0.130, 0.134
0.153, 0.022
0.157, 0.165
0.173, 0.030
0.180, 0.193
0.195, 0.038
0.207, 0.229
0.233, 0.040
0.246, 0.272
0.257, 0.044
0.272, 0.302
0.285, 0.048
0.303, 0.340
0.315, 0.062
0.345, 0.406
0.336, 0.057
0.362, 0.413
0.368, 0.077
0.416, 0.510
0.394, 0.084
0.450, 0.561
0.431, 0.092
0.498, 0.631
0.458, 0.100
0.538, 0.697
Table 5: Model sea-level projections, and allowances for Wellington under RCP4.5. The third
column shows the range of model projections expressed as the best estimate (central value),
∆z, and standard deviation, σm . The ‘very likely’ allowance, A, involves the assumption that
the ‘very likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%)
range of projection uncertainty. The ‘likely’ allowance, A, is a more conservative estimate,
involving the assumption that not all the uncertainty is captured by the models so that the
‘very likely’ (5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of
projection uncertainty.
17
Effective average recurrence interval (years)
Height (m) 1.50 1.60 1.70 1.80 1.86 1.90 1.92 2.00 2.07 2.10 2.20 2.23 2.30 2.38
Year
2015
0.0 0.0 0.1 0.2 0.3 0.5 0.6 1.4 3.0 4.1 11.6 16.0 33.2 76.8
2020
0.0 0.0 0.1 0.1 0.3 0.4 0.5 1.2 2.5 3.4 9.8 13.4 27.9 64.6
2025
0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.9 1.9 2.6 7.4 10.1 21.1 48.8
2030
0.0 0.0 0.0 0.1 0.2 0.2 0.3 0.7 1.4 1.9 5.5 7.5 15.6 36.1
2035
0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.5 1.0 1.4 3.9 5.3 11.1 25.6
2040
0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 0.7 1.0 2.8 3.9 8.0 18.6
2045
0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 0.6 0.8 2.2 3.0 6.2 14.4
2050
0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4 0.6 1.6 2.2 4.5 10.5
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 1.0 1.4 2.9 6.8
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.7 1.0 2.1 4.8
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.6 0.8 1.6 3.7
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.4 0.5 1.0 2.4
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 0.8 1.8
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.6 1.3
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.4 0.9
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2
Table 6: Effective average recurrence intervals (EARIs) for Auckland under RCP4.5 using the
‘very likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
18
Effective average recurrence interval (years)
Height (m) 1.50 1.60 1.70 1.80 1.86 1.90 1.92 2.00 2.07 2.10 2.20 2.23 2.30 2.38
Year
2015
0.0 0.0 0.1 0.2 0.3 0.5 0.6 1.4 3.0 4.1 11.6 16.0 33.2 76.8
2020
0.0 0.0 0.1 0.1 0.3 0.4 0.5 1.2 2.5 3.4 9.8 13.4 27.9 64.6
2025
0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.9 1.9 2.6 7.4 10.1 21.0 48.7
2030
0.0 0.0 0.0 0.1 0.2 0.2 0.3 0.7 1.4 1.9 5.4 7.4 15.5 35.8
2035
0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.5 1.0 1.3 3.8 5.2 10.9 25.2
2040
0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 0.7 1.0 2.7 3.8 7.8 18.1
2045
0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 0.5 0.7 2.1 2.9 6.0 14.0
2050
0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4 0.5 1.4 1.9 4.0 9.3
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.8 1.1 2.2 5.2
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.6 0.8 1.6 3.6
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4 0.6 1.2 2.8
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.7 1.5
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2 0.5 1.1
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.7
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
Table 7: Effective average recurrence intervals (EARIs) for Auckland under RCP4.5 using
the ‘likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
19
Effective average recurrence interval (years)
Height (m) 1.18 1.20 1.28 1.30 1.40 1.42 1.50 1.53 1.60 1.67 1.70 1.76 1.80 1.90
Year
2015
0.0 0.0 0.1 0.1 0.3 0.4 1.1 1.6 3.7 8.8 12.7 26.5 43.3 148.2
2020
0.0 0.0 0.1 0.1 0.2 0.3 0.8 1.2 2.8 6.7 9.6 20.1 32.9 112.6
2025
0.0 0.0 0.0 0.1 0.2 0.2 0.6 0.9 2.0 4.8 7.0 14.6 23.9 81.7
2030
0.0 0.0 0.0 0.0 0.1 0.2 0.4 0.6 1.4 3.3 4.8 10.0 16.4 56.0
2035
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 1.0 2.4 3.4 7.2 11.7 40.0
2040
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.7 1.6 2.4 4.9 8.1 27.5
2045
0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5 1.2 1.7 3.6 5.9 20.2
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.8 1.1 2.4 3.9 13.2
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5 0.7 1.5 2.5 8.4
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.5 1.0 1.7 5.7
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.3 0.4 0.8 1.3 4.4
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2 0.5 0.8 2.7
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.5 1.5
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 1.1
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.7
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.4
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
Table 8: Effective average recurrence intervals (EARIs) for Dunedin under RCP4.5 using the
‘very likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
20
Effective average recurrence interval (years)
Height (m) 1.18 1.20 1.28 1.30 1.40 1.42 1.50 1.53 1.60 1.67 1.70 1.76 1.80 1.90
Year
2015
0.0 0.0 0.1 0.1 0.3 0.4 1.1 1.6 3.7 8.8 12.7 26.5 43.3 148.2
2020
0.0 0.0 0.1 0.1 0.2 0.3 0.8 1.2 2.8 6.7 9.6 20.1 32.9 112.6
2025
0.0 0.0 0.0 0.1 0.2 0.2 0.6 0.9 2.0 4.8 6.9 14.4 23.6 80.6
2030
0.0 0.0 0.0 0.0 0.1 0.1 0.4 0.6 1.4 3.2 4.7 9.7 15.9 54.5
2035
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 0.9 2.2 3.2 6.7 11.0 37.6
2040
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.6 1.5 2.2 4.6 7.6 26.0
2045
0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5 1.1 1.6 3.3 5.5 18.7
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.6 0.9 1.9 3.2 10.9
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.5 1.0 1.7 5.8
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.7 1.2 4.0
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2 0.5 0.8 2.8
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 1.4
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.6
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.5
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 9: Effective average recurrence intervals (EARIs) for Dunedin under RCP4.5 using the
‘likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
21
Effective average recurrence interval (years)
Height (m) 1.37 1.40 1.50 1.52 1.55 1.60 1.66 1.68 1.70 1.71 1.72 1.74 1.80 1.90
Year
2015
0.0 0.0 0.1 0.1 0.2 0.4 1.0 1.4 1.8 2.1 2.5 3.4 8.5 39.3
2020
0.0 0.0 0.1 0.1 0.2 0.4 0.9 1.2 1.6 1.9 2.2 3.0 7.6 35.0
2025
0.0 0.0 0.0 0.1 0.1 0.2 0.6 0.8 1.0 1.2 1.4 1.9 4.8 22.3
2030
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.5 0.6 0.7 0.9 1.2 2.9 13.4
2035
0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.5 0.7 1.8 8.4
2040
0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2 0.3 0.3 0.4 0.5 1.3 6.0
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.2 0.3 0.8 3.8
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.2 0.2 0.5 2.4
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.3 1.5
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.8
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.6
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.4
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 10: Effective average recurrence intervals (EARIs) for Lyttleton under RCP4.5 using
the ‘very likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very
likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of
projection uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the
assumption that not all the uncertainty is captured by the models so that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of projection
uncertainty.)
22
Effective average recurrence interval (years)
Height (m) 1.37 1.40 1.50 1.52 1.55 1.60 1.66 1.68 1.70 1.71 1.72 1.74 1.80 1.90
Year
2015
0.0 0.0 0.1 0.1 0.2 0.4 1.0 1.4 1.8 2.1 2.5 3.4 8.5 39.3
2020
0.0 0.0 0.1 0.1 0.2 0.4 0.9 1.2 1.6 1.9 2.2 3.0 7.6 35.0
2025
0.0 0.0 0.0 0.1 0.1 0.2 0.6 0.8 1.0 1.2 1.4 1.9 4.8 22.0
2030
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 0.6 0.7 0.8 1.1 2.8 12.8
2035
0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.4 0.5 0.7 1.7 7.9
2040
0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.3 0.4 0.5 1.2 5.7
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.2 0.3 0.7 3.4
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.2 0.4 2.0
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.2 1.1
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.6
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.3
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 11: Effective average recurrence intervals (EARIs) for Lyttleton under RCP4.5 using
the ‘likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
23
Effective average recurrence interval (years)
Height (m) 0.78 0.80 0.84 0.90 0.99 1.00 1.05 1.10 1.11 1.12 1.20 1.30 1.31 1.32
Year
2015
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.7 0.8 1.0 3.5 17.4 20.4 24.0
2020
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5 0.6 0.7 2.6 12.7 14.9 17.5
2025
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4 0.4 0.5 1.8 8.8 10.3 12.1
2030
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.3 1.1 5.3 6.3 7.3
2035
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.7 3.5 4.1 4.8
2040
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.4 2.2 2.6 3.0
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 1.4 1.7 1.9
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 1.0 1.2 1.4
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.6 0.7 0.9
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.3 0.4 0.5
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.3 0.3
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 12: Effective average recurrence intervals (EARIs) for Wellington under RCP4.5 using
the ‘very likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very
likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of
projection uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the
assumption that not all the uncertainty is captured by the models so that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of projection
uncertainty.)
24
Effective average recurrence interval (years)
Height (m) 0.78 0.80 0.84 0.90 0.99 1.00 1.05 1.10 1.11 1.12 1.20 1.30 1.31 1.32
Year
2015
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.7 0.8 1.0 3.5 17.4 20.4 24.0
2020
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5 0.6 0.7 2.6 12.7 14.9 17.5
2025
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4 0.4 0.5 1.8 8.7 10.2 11.9
2030
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2 0.3 1.0 5.1 6.0 7.1
2035
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.6 3.1 3.7 4.3
2040
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.4 2.0 2.4 2.8
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 1.3 1.5 1.7
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.8 0.9 1.1
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.4 0.5 0.6
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.3 0.3
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 13: Effective average recurrence intervals (EARIs) for Wellington under RCP4.5 using
the ‘likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
25
Year
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
2065
2070
2075
2080
2085
2090
2095
2100
Model projection
‘very likely’ range
5,95% (metres)
0.000, 0.000
0.005, 0.039
0.034, 0.065
0.064, 0.091
0.085, 0.125
0.133, 0.165
0.140, 0.211
0.167, 0.258
0.200, 0.319
0.223, 0.373
0.263, 0.443
0.296, 0.522
0.307, 0.587
0.358, 0.647
0.382, 0.730
0.407, 0.832
0.460, 0.899
0.503, 1.009
Model projection
Allowance, A
∆z, σm
‘very likely’, ‘likely’
(metres)
(metres)
0.000, 0.000
0.000, 0.000
0.022, 0.010
0.022, 0.024
0.050, 0.009
0.050, 0.051
0.078, 0.008
0.078, 0.079
0.105, 0.012
0.106, 0.107
0.149, 0.010
0.149, 0.150
0.175, 0.022
0.178, 0.183
0.213, 0.028
0.217, 0.225
0.260, 0.036
0.266, 0.280
0.298, 0.046
0.309, 0.331
0.353, 0.055
0.369, 0.400
0.409, 0.069
0.434, 0.483
0.447, 0.085
0.485, 0.560
0.503, 0.088
0.543, 0.623
0.556, 0.106
0.614, 0.730
0.619, 0.129
0.707, 0.880
0.680, 0.133
0.773, 0.957
0.756, 0.154
0.880, 1.124
Table 14: Model sea-level projections, and allowances for Auckland under RCP8.5. The third
column shows the range of model projections expressed as the best estimate (central value),
∆z, and standard deviation, σm . The ‘very likely’ allowance, A, involves the assumption that
the ‘very likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%)
range of projection uncertainty. The ‘likely’ allowance, A, is a more conservative estimate,
involving the assumption that not all the uncertainty is captured by the models so that the
‘very likely’ (5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of
projection uncertainty.
26
Year
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
2065
2070
2075
2080
2085
2090
2095
2100
Model projection
‘very likely’ range
5,95% (metres)
0.000, 0.000
-0.010, 0.046
0.030, 0.068
0.062, 0.078
0.098, 0.118
0.123, 0.165
0.125, 0.229
0.153, 0.272
0.196, 0.312
0.222, 0.376
0.267, 0.434
0.288, 0.523
0.306, 0.595
0.359, 0.654
0.390, 0.725
0.399, 0.838
0.455, 0.897
0.494, 1.010
Model projection
Allowance, A
∆z, σm
‘very likely’, ‘likely’
(metres)
(metres)
0.000, 0.000
0.000, 0.000
0.018, 0.017
0.020, 0.024
0.049, 0.011
0.050, 0.051
0.070, 0.005
0.070, 0.071
0.108, 0.006
0.108, 0.108
0.144, 0.013
0.145, 0.147
0.177, 0.031
0.183, 0.195
0.212, 0.036
0.221, 0.237
0.254, 0.035
0.262, 0.277
0.299, 0.047
0.312, 0.339
0.351, 0.051
0.366, 0.398
0.405, 0.071
0.436, 0.498
0.450, 0.088
0.498, 0.591
0.506, 0.090
0.556, 0.653
0.557, 0.102
0.621, 0.746
0.619, 0.133
0.728, 0.944
0.676, 0.135
0.787, 1.007
0.752, 0.157
0.904, 1.202
Table 15: Model sea-level projections, and allowances for Dunedin under RCP8.5. The third
column shows the range of model projections expressed as the best estimate (central value),
∆z, and standard deviation, σm . The ‘very likely’ allowance, A, involves the assumption that
the ‘very likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%)
range of projection uncertainty. The ‘likely’ allowance, A, is a more conservative estimate,
involving the assumption that not all the uncertainty is captured by the models so that the
‘very likely’ (5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of
projection uncertainty.
27
Year
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
2065
2070
2075
2080
2085
2090
2095
2100
Model projection
‘very likely’ range
5,95% (metres)
0.000, 0.000
0.014, 0.023
0.045, 0.051
0.079, 0.079
0.102, 0.115
0.130, 0.169
0.129, 0.225
0.149, 0.268
0.189, 0.316
0.229, 0.355
0.263, 0.420
0.295, 0.506
0.312, 0.551
0.373, 0.616
0.388, 0.704
0.434, 0.790
0.465, 0.880
0.508, 0.963
Model projection
Allowance, A
∆z, σm
‘very likely’, ‘likely’
(metres)
(metres)
0.000, 0.000
0.000, 0.000
0.019, 0.003
0.019, 0.019
0.048, 0.002
0.048, 0.048
0.079, 0.000
0.079, 0.079
0.108, 0.004
0.108, 0.109
0.150, 0.012
0.151, 0.153
0.177, 0.029
0.183, 0.196
0.209, 0.036
0.219, 0.239
0.252, 0.039
0.264, 0.286
0.292, 0.038
0.303, 0.325
0.342, 0.048
0.359, 0.393
0.400, 0.064
0.432, 0.494
0.432, 0.073
0.472, 0.552
0.495, 0.074
0.536, 0.619
0.546, 0.096
0.617, 0.756
0.612, 0.108
0.702, 0.879
0.673, 0.126
0.795, 1.035
0.736, 0.138
0.882, 1.170
Table 16: Model sea-level projections, and allowances for Lyttleton under RCP8.5. The third
column shows the range of model projections expressed as the best estimate (central value),
∆z, and standard deviation, σm . The ‘very likely’ allowance, A, involves the assumption that
the ‘very likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%)
range of projection uncertainty. The ‘likely’ allowance, A, is a more conservative estimate,
involving the assumption that not all the uncertainty is captured by the models so that the
‘very likely’ (5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of
projection uncertainty.
28
Year
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
2065
2070
2075
2080
2085
2090
2095
2100
Model projection
‘very likely’ range
5,95% (metres)
0.000, 0.000
0.030, 0.037
0.061, 0.062
0.074, 0.093
0.098, 0.117
0.118, 0.175
0.128, 0.217
0.156, 0.253
0.173, 0.321
0.220, 0.350
0.261, 0.427
0.278, 0.509
0.314, 0.540
0.348, 0.624
0.379, 0.686
0.418, 0.762
0.455, 0.855
0.486, 0.961
Model projection
Allowance, A
∆z, σm
‘very likely’, ‘likely’
(metres)
(metres)
0.000, 0.000
0.000, 0.000
0.033, 0.002
0.033, 0.034
0.061, 0.000
0.061, 0.061
0.083, 0.006
0.084, 0.084
0.107, 0.006
0.108, 0.108
0.146, 0.017
0.149, 0.154
0.173, 0.027
0.178, 0.190
0.205, 0.029
0.211, 0.225
0.247, 0.045
0.264, 0.295
0.285, 0.040
0.297, 0.322
0.344, 0.050
0.364, 0.405
0.394, 0.070
0.433, 0.510
0.427, 0.069
0.465, 0.539
0.486, 0.084
0.543, 0.654
0.533, 0.093
0.603, 0.740
0.590, 0.105
0.677, 0.850
0.655, 0.122
0.773, 1.006
0.723, 0.144
0.890, 1.219
Table 17: Model sea-level projections, and allowances for Wellington under RCP8.5. The third
column shows the range of model projections expressed as the best estimate (central value),
∆z, and standard deviation, σm . The ‘very likely’ allowance, A, involves the assumption that
the ‘very likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%)
range of projection uncertainty. The ‘likely’ allowance, A, is a more conservative estimate,
involving the assumption that not all the uncertainty is captured by the models so that the
‘very likely’ (5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of
projection uncertainty.
29
Effective average recurrence interval (years)
Height (m) 1.50 1.60 1.70 1.80 1.86 1.90 1.92 2.00 2.07 2.10 2.20 2.23 2.30 2.38
Year
2015
0.0 0.0 0.1 0.2 0.3 0.5 0.6 1.4 3.0 4.1 11.6 16.0 33.2 76.8
2020
0.0 0.0 0.0 0.1 0.3 0.4 0.5 1.1 2.4 3.2 9.2 12.6 26.3 60.8
2025
0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.8 1.8 2.4 6.9 9.4 19.7 45.4
2030
0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.6 1.3 1.8 5.1 7.0 14.7 33.9
2035
0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.5 1.0 1.3 3.8 5.3 11.0 25.4
2040
0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 0.6 0.9 2.4 3.3 6.9 16.1
2045
0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.2 0.5 0.6 1.8 2.5 5.1 11.9
2050
0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 0.4 1.2 1.6 3.4 7.9
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.7 1.0 2.0 4.7
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5 0.6 1.3 3.0
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.7 1.6
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.4 0.8
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 18: Effective average recurrence intervals (EARIs) for Auckland under RCP8.5 using
the ‘very likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very
likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of
projection uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the
assumption that not all the uncertainty is captured by the models so that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of projection
uncertainty.)
30
Effective average recurrence interval (years)
Height (m) 1.50 1.60 1.70 1.80 1.86 1.90 1.92 2.00 2.07 2.10 2.20 2.23 2.30 2.38
Year
2015
0.0 0.0 0.1 0.2 0.3 0.5 0.6 1.4 3.0 4.1 11.6 16.0 33.2 76.8
2020
0.0 0.0 0.0 0.1 0.3 0.4 0.5 1.1 2.3 3.2 9.1 12.5 26.0 60.1
2025
0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.8 1.7 2.4 6.8 9.3 19.5 45.0
2030
0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.6 1.3 1.8 5.1 7.0 14.6 33.7
2035
0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.5 1.0 1.3 3.8 5.2 10.8 25.0
2040
0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 0.6 0.8 2.4 3.3 6.9 15.9
2045
0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4 0.6 1.7 2.3 4.9 11.3
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 1.1 1.5 3.2 7.3
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2 0.6 0.8 1.8 4.1
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.4 0.5 1.0 2.4
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2 0.5 1.2
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 19: Effective average recurrence intervals (EARIs) for Auckland under RCP8.5 using
the ‘likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
31
Effective average recurrence interval (years)
Height (m) 1.18 1.20 1.28 1.30 1.40 1.42 1.50 1.53 1.60 1.67 1.70 1.76 1.80 1.90
Year
2015
0.0 0.0 0.1 0.1 0.3 0.4 1.1 1.6 3.7 8.8 12.7 26.5 43.3 148.2
2020
0.0 0.0 0.1 0.1 0.2 0.3 0.8 1.2 2.9 6.8 9.9 20.7 33.9 115.9
2025
0.0 0.0 0.0 0.1 0.2 0.2 0.6 0.8 2.0 4.7 6.9 14.3 23.4 80.2
2030
0.0 0.0 0.0 0.0 0.1 0.2 0.5 0.7 1.6 3.7 5.3 11.1 18.2 62.3
2035
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 1.0 2.3 3.4 7.0 11.5 39.3
2040
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.6 1.5 2.1 4.5 7.3 25.0
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.4 0.9 1.3 2.8 4.6 15.6
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.6 0.8 1.8 2.9 9.8
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.4 0.5 1.1 1.7 5.9
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.6 0.9 3.2
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.5 1.6
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.7
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 20: Effective average recurrence intervals (EARIs) for Dunedin under RCP8.5 using the
‘very likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
32
Effective average recurrence interval (years)
Height (m) 1.18 1.20 1.28 1.30 1.40 1.42 1.50 1.53 1.60 1.67 1.70 1.76 1.80 1.90
Year
2015
0.0 0.0 0.1 0.1 0.3 0.4 1.1 1.6 3.7 8.8 12.7 26.5 43.3 148.2
2020
0.0 0.0 0.1 0.1 0.2 0.3 0.8 1.2 2.8 6.6 9.5 19.8 32.4 111.0
2025
0.0 0.0 0.0 0.0 0.2 0.2 0.6 0.8 2.0 4.6 6.7 14.1 23.0 78.7
2030
0.0 0.0 0.0 0.0 0.1 0.2 0.5 0.7 1.6 3.7 5.3 11.1 18.2 62.1
2035
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 1.0 2.3 3.3 7.0 11.4 39.1
2040
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 0.6 1.4 2.1 4.4 7.1 24.4
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.8 1.1 2.4 3.9 13.4
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.5 0.7 1.4 2.4 8.1
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 0.9 1.4 4.9
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4 0.7 2.3
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.3 1.1
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 21: Effective average recurrence intervals (EARIs) for Dunedin under RCP8.5 using
the ‘likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
33
Effective average recurrence interval (years)
Height (m) 1.37 1.40 1.50 1.52 1.55 1.60 1.66 1.68 1.70 1.71 1.72 1.74 1.80 1.90
Year
2015
0.0 0.0 0.1 0.1 0.2 0.4 1.0 1.4 1.8 2.1 2.5 3.4 8.5 39.3
2020
0.0 0.0 0.1 0.1 0.1 0.3 0.7 1.0 1.4 1.6 1.9 2.5 6.4 29.4
2025
0.0 0.0 0.0 0.1 0.1 0.2 0.5 0.7 0.9 1.0 1.2 1.6 4.1 18.9
2030
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 0.6 0.6 0.7 1.0 2.5 11.8
2035
0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.4 0.5 0.6 1.6 7.5
2040
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.2 0.3 0.8 3.9
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.2 0.2 0.5 2.4
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.3 1.4
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.7
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.4
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 22: Effective average recurrence intervals (EARIs) for Lyttleton under RCP8.5 using
the ‘very likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very
likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of
projection uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the
assumption that not all the uncertainty is captured by the models so that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of projection
uncertainty.)
34
Effective average recurrence interval (years)
Height (m) 1.37 1.40 1.50 1.52 1.55 1.60 1.66 1.68 1.70 1.71 1.72 1.74 1.80 1.90
Year
2015
0.0 0.0 0.1 0.1 0.2 0.4 1.0 1.4 1.8 2.1 2.5 3.4 8.5 39.3
2020
0.0 0.0 0.1 0.1 0.1 0.3 0.7 1.0 1.4 1.6 1.9 2.5 6.3 29.3
2025
0.0 0.0 0.0 0.1 0.1 0.2 0.5 0.7 0.9 1.0 1.2 1.6 4.1 18.9
2030
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 0.6 0.6 0.7 1.0 2.5 11.8
2035
0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 0.3 0.4 0.5 0.6 1.6 7.5
2040
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.2 0.2 0.3 0.8 3.8
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.2 0.4 1.9
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.2 1.0
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.5
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.3
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 23: Effective average recurrence intervals (EARIs) for Lyttleton under RCP8.5 using
the ‘likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
35
Effective average recurrence interval (years)
Height (m) 0.78 0.80 0.84 0.90 0.99 1.00 1.05 1.10 1.11 1.12 1.20 1.30 1.31 1.32
Year
2015
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.7 0.8 1.0 3.5 17.4 20.4 24.0
2020
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4 0.5 0.6 2.1 10.2 12.0 14.0
2025
0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.3 0.4 1.3 6.5 7.7 9.0
2030
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2 0.3 0.9 4.6 5.4 6.3
2035
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.2 0.6 3.1 3.6 4.3
2040
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 1.6 1.9 2.2
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 1.0 1.2 1.4
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.6 0.7 0.8
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.3 0.3 0.4
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 24: Effective average recurrence intervals (EARIs) for Wellington under RCP8.5 using
the ‘very likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very
likely’ (5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of
projection uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the
assumption that not all the uncertainty is captured by the models so that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘likely’ (17-83%) range of projection
uncertainty.)
36
Effective average recurrence interval (years)
Height (m) 0.78 0.80 0.84 0.90 0.99 1.00 1.05 1.10 1.11 1.12 1.20 1.30 1.31 1.32
Year
2015
0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.7 0.8 1.0 3.5 17.4 20.4 24.0
2020
0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.4 0.5 0.6 2.1 10.2 11.9 14.0
2025
0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.3 0.4 1.3 6.5 7.7 9.0
2030
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2 0.3 0.9 4.5 5.3 6.2
2035
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.2 0.6 3.1 3.6 4.2
2040
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.3 1.5 1.7 2.0
2045
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.8 1.0 1.1
2050
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.5 0.6 0.7
2055
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.2 0.2
2060
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1
2065
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2070
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2075
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2080
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2085
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2090
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2095
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2100
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 25: Effective average recurrence intervals (EARIs) for Wellington under RCP8.5 using
the ‘likely’ assumption. (The ‘very likely’ EARI involves the assumption that the ‘very likely’
(5-95%) range of model uncertainty approximates the ‘very likely’ (5-95%) range of projection
uncertainty. The ‘likely’ EARI is a more conservative estimate, involving the assumption that
not all the uncertainty is captured by the models so that the ‘very likely’ (5-95%) range of
model uncertainty approximates the ‘likely’ (17-83%) range of projection uncertainty.)
37
6
Glossary of Terms
AR4 Fourth Assessment Report of the Intergovernmental Panel on Climate Change.
AR5 Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
ARI Average recurrence interval.
EARI Effective ARI, obtained by taking the reciprocal of the result of averaging the
reciprocal ARI over the range of projected sea-level rise.
GIA Glacial isostatic adjustment (the continuing response of the ocean surface and Earth’s
crust to the end of the last glaciation).
IPCC Intergovernmental Panel on Climate Change.
OPCE Office of the Parliamentary Commissioner for the Environment, Wellington, New
Zealand
RCP Representative Concentration Pathway (prescribed concentrations of greenhouse gases
and aerosols that are used to force the climate models described by the IPCC AR5).
Relative sea-level rise The sea-level rise relative to the land.
Sea-level planning allowance The vertical distance that a coastal entity needs to be
raised in order to cope with the projected sea-level rise.
SRES Special Report on Emission Scenarios (Nakicenovic et al, 2000).
Storm tide The combination of tide and storm surge.
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39
Appendix A
Copy of Contract
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15 July 2015